Extended Data Fig. 2: Linear probe results for molecular classification tasks.
From: A multimodal whole-slide foundation model for pathology
(a) Linear models are fitted and evaluated on binary molecular status predictions for BCNB and MUT-HET. We observe that TITAN consistently performs best with + 0.9% on BCNB and MUT-HET, +1.7% on TCGA, and +3.7% on internal molecular classification of BRCA and LUAD, in averaged AUROC scores over the next best model PRISM. (b) Linear models are fitted and evaluated on five-fold splits on TCGA. (c) The same models are evaluated on the corresponding external datasets from CPTAC and EBRAINS. (d) 6-level ER and PR prediction from Mass General Hospital (MGH) and 3-level PD-L1 prediction, all from immunohistochemistry (IHC) slides. (e) Molecular classification tasks for BRCA and LUAD from Mass General Brigham (MGB). All error bars represent standard deviations based on bootstrapping (n = 1,000) or k-fold evaluation (k = 5).
